Machine condition monitoring generally concerns the use of various types of sensors and data analysis to assess the operating state of various types of machinery. Through the detection of trends, specific patterns or anomalous data from such sensor readings, atypical machine operation may be addressed, potentially before failure of the relevant machinery. In this manner, costly breakdowns can be avoided.
A particular subset of machine condition monitoring concerns various types of machines having rotating components. For example, a machine having a rotating shaft or the like typically employs one or more bearing assemblies. A common problem for such equipment is the eventual degradation and ultimate failure of such bearings. Condition monitoring systems as applied to rotating components often rely on the use of rotation detection sensors, also called rotary encoders or shaft encoders (hereinafter rotation sensors), that are common electro-mechanical devices that convert the angular position or motion of a shaft or axle to an analog or digital code. Such systems often employ other types of sensors to detect vibrations, temperature, etc. of the machinery being monitored. The resulting collection of sensor data may be analyzed according to various well-known techniques to assess, and possibly predict the imminent failure of, the rotating components.
Even though condition monitoring systems have been used for a number of years, the attendant cost of, or difficulty deploying, such systems is often prohibitive for many applications. As a result, many systems must rely on in-person audits rather than real time continuous monitoring. Consequently, machinery may go for relatively extended periods of time without any type of monitoring and, accordingly, the likelihood of untimely failure cannot be mitigated.
Thus, condition monitoring solutions that are both cost-effective and comparatively easy to deploy would represent a welcome advance in the art.